This paper is in the following e-collection/theme issue:

Reviews in AI (18) Applications of AI (229)

Published on in Vol 3 (2024)

This is a member publication of University of Toronto

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/57983, first published .
Exploring Machine Learning Applications in Pediatric Asthma Management: Scoping Review

Exploring Machine Learning Applications in Pediatric Asthma Management: Scoping Review

Exploring Machine Learning Applications in Pediatric Asthma Management: Scoping Review

Authors of this article:

Tanvi Ojha1, 2 Author Orcid Image ;   Atushi Patel1 Author Orcid Image ;   Krishihan Sivapragasam1 Author Orcid Image ;   Radha Sharma1, 2 Author Orcid Image ;   Tina Vosoughi1 Author Orcid Image ;   Becky Skidmore3 Author Orcid Image ;   Andrew D Pinto1, 4, 5, 6 Author Orcid Image ;   Banafshe Hosseini1, 5, 6 Author Orcid Image
Article Authors Cited by (5) Tweetations (7) Metrics

Journals

  1. Lisik D, Basna R, Dinh T, Hennig C, Shah S, Wennergren G, Goksör E, Nwaru B. Artificial intelligence in pediatric allergy research. European Journal of Pediatrics 2024;184(1) View
  2. Coleman L, Khoo S, Franks K, Prastanti F, Leffler J, Le Souëf P, Karpievitch Y, Hancock D, Laing I. Clinical Predictors of Longitudinal Respiratory Exacerbation Outcomes in Young Hospitalised Children. Clinical & Experimental Allergy 2025 View
  3. Adamu Aliyu D, Akashah Patah Akhir E, Omar Abdullah Sawad M, Shehu Yalli J, Saidu Y. A Reinforcement Learning Approach to Personalized Asthma Exacerbation Prediction Using Proximal Policy Optimization. IEEE Access 2025;13:103373 View
  4. Alkobaisi S, Bae W, Safdar M, Abu Ali N, Kim S, Park C, Nowak R, Kakulapati V. A hybrid approach for forecasting peak expiratory flow rate in asthma patients using combined linear regression and random forest model. PLOS One 2025;20(8):e0326036 View

Conference Proceedings

  1. AnilKumar N, K D, Ghantasala G, Soans S, Satapathi G, Pandey S. 2025 International Conference on Computing Technologies (ICOCT). Pediatric Cough Classification for Respiratory Conditions using a Modified SqueezeNet Model View